Potential of hyperspectral imaging for nondestructive determination of α-farnesene and conjugated trienol content in 'Yali ' pear

文献类型： 外文期刊

第一作者： Cheng, Hong

作者： Cheng, Hong;Zhang, Zishen;Cheng, Yudou;Guan, Junfeng;Cheng, Hong;Zhang, Zishen;Cheng, Yudou;Guan, Junfeng;Zhang, Zishen

作者机构：

关键词： Hyperspectral imaging; 'Yali' pear; Superficial scald; alpha-Farnesene; Conjugated trienols

期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.3； 五年影响因子：3.8 ）

ISSN： 1386-1425

年卷期： 2024 年 321 卷

页码：

收录情况： SCI

摘要： The sesquiterpene alpha-farnesene and its corresponding oxidation products, namely conjugated trienols (CTols) is well known to be correlated with the development of superficial scald, a typical physiological disorder after a long term of cold storage in pear fruit. In this work, hyperspectral imaging (HSI) technology was used for nondestructive predicting of alpha-farnesene and CTols [CT258, CT281 and CT(281-290)] content in 'Yali ' pear. In order to obtain the best performance of calibration model and simplify the calibration model further, various preprocessing methods together with their combinations and different wavelength selection algorithms, including successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE), were investigated and compared based on linear partial least square regression (PLSR) and nonlinear least square support vector machine (LS-SVM) models, respectively. In conclusion, compared to the PLSR models, the results of LS-SVM models based on original and preprocessing methods performed better for the prediction of alpha-farnesene and CTols, while the performance of LS-SVM models based on the selected characteristic wavelengths were worse. For alpha-farnesene, the best result was obtained by LSSVM model based on MSC-FD pretreatment with the RPD value of 2.6, R p = 0.925 and RMSEP = 4.387 nmol cm-2 . And for CTols, CT281 performed better compared with CT258 and CT(281-290), achieving the result with RPD = 2.4, R p = 0.913 and RMSEP = 2.734 nmol cm-2 based on LS-SVM model combined with SD pretreatment. The overall results illustrated HSI technology could be used for rapid and nondestructive prediction of alpha-farnesene and CTols in 'Yali' pear, which would be helpful for supporting postharvest decision systems.

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